RNA-seq Analysis

In this computer lab module, students learn how to process an RNA-seq data set to identify differentially expressed genes (DEGs). The samples for this data set were collected from yeast cells expressing either a control gene or a pathogen effector gene. The goal is to identify potential cellular targets of the pathogen protein based on the global transcriptional response. Students access and analyze the RNA-seq data set using a publicly available Galaxy server. After checking and processing the data for quality control, they then map the reads to the yeast reference genome and subsequently identify genes that are differentially expressed between the control and experimental samples. 

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Statement from the author (Bill Morgan):

This is the final module in my semester-long course-embedded research project. In prior modules, students learn most of the background on this study. Since these modules aren't included here, additional background content should be developed to allow the activity to stand alone.  Alternatively, the module might be made less specific to my RNA-seq data set, so that it could be used with user-supplied data. To allow this and to deal with constant software updates, a separate "tip sheet" wiki can be used. 

Statement from the managing editor (Sam Donovan):

We think that there is a lot of potential for this unit to help students experience the use of bioinformatics approaches to solving biological problems.

Incubator start and end times:

This Incubator will run from September 1, 2016 to October 1, 2016. 

QUBES Liaison: Hayley Orndorf